| |
Apr 25, 2024
|
|
|
|
|
MATH 5630 - Discrete Modeling and Optimization
Modeling and solving real-life problems by discrete optimization techniques. The discrete models include integer programming, dynamic programming, network optimization problems. Applications in large economic systems, scheduling, voting theory, telecom and transportation networks are discussed.
Requisites:
Credit Hours: 3
Repeat/Retake Information: May not be retaken.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Students will know how to build optimization models using binary integer variables, dynamic programs, and mathematical networks.
- Analyze the algorithms in terms of their accuracy and efficiency.
- Apply algorithms to solve the optimization problems.
- Understand the theory behind the algorithms.
Add to Portfolio (opens a new window)
|
|
